There are a number of situations in which it may be desirable to monitor a patient via one or more sensors. For example, it may be desirable to monitor the progression of an ailment or symptoms of the patient via one or more sensors. As another example, the efficacy of a treatment delivered to the patient may be monitored via one or more sensors. Furthermore, a medical device may control delivery of a therapy, e.g., provide closed-loop therapy, based on signals from one or more patient sensors.
In some cases, as an example, an ailment may affect a patient's activity level or range of activities by preventing the patient from being active. For example, chronic pain may cause a patient to avoid particular physical activities, or physical activity in general, where such activities increase the pain experienced by the patient. When a patient is inactive, he or she may be more likely to be recumbent, i.e., lying down, or sitting, and may change postures less frequently. Other ailments that may affect patient activity include movement disorders such as tremor, Parkinson's disease, multiple sclerosis, epilepsy, spasticity, or other neurological disorders, such as psychological or mood disorders, which may result in irregular movement or activity, or a generally decreased level of activity. In such cases, it may be desirable to monitor the patient with one or more sensors that generate a signal as a function of patient activity, motion, and/or posture.
In some cases, these ailments are treated via a medical device, such as an implantable medical device (IMD). For example, patients may receive an implantable neurostimulator or drug delivery device to treat chronic pain, a movement disorder, or a psychological disorder. The IMD, or some other system component in communication with the IMD, may collect objective data based on signals generated by one or more sensors. The IMD, other system component, patient, or a clinician may use the sensor data to, for example, evaluate symptom progression or therapy efficacy, optimize the therapy, or provide closed-loop feedback control of the therapy.
Other example situations in which patient sensors may be used to provide feedback for controlling the delivery of a therapy to a patient by an IMD are spinal cord stimulation and cardiac pacing. In the case of spinal cord stimulation, an activity, motion, or posture sensor may be used to control the intensity, e.g., amplitude or rate, of the electrical stimulation delivered to the spinal cord to alleviate pain. Adjusting the stimulation intensity in this manner may compensate for activity-dependent or posture-dependent changes in pain intensity or location, which may in by due, in part, to changes in the position of electrodes relative to the spinal cord. In the case of cardiac pacing, the rate of pacing may be adjusted as a function of patient demand. Patient demand may be indicated by, for example, patient activity, motion, or posture.
One example of a sensor capable of detecting patient posture, motion, and activity is an accelerometer, such as a multi-axis accelerometer. A three-axis accelerometer, for example, may be able to detect motion and posture by detecting acceleration along three axes. Another example of a sensor capable of detecting posture, motion, or activity is a mercury switch sensor, an example of which is described in commonly-assigned U.S. Pat. No. 5,031,618, to Mullett.
Generally, a clinician uses a programmer, e.g., a computing device capable of communicating with implantable medical devices via local device telemetry, to program an implantable medical device for delivery of therapy to a patient. In some cases, such clinician programmers take the form of handheld and/or tablet-type computing devices. Handheld and/or tablet-type clinician programmers can allow for a more natural “bedside” interaction between clinicians and patients during the programming process. Handheld and/or tablet-type clinician programmers can also allow the programmer to be handed off to the patient for entry of symptom, therapy efficacy, or other patient data.